The authors present research methodology and outcomes, which is relevant to probabilistic genotyping for investigative purposes.
This is the credible genotype set and is used to inform database search criteria. Within this work, the authors demonstrate the salience of single-cell analysis by performance testing a set of 630 previously constructed admixtures containing up to five donors of balanced and unbalanced contributions. The authors use scEPGs that were generated by isolating single cells, employing a direct-to-PCR extraction treatment, amplifying STRs that are compliant with existing national databases and applying post-PCR treatments that elicit a detection limit of one DNA copy. They determined that, for these test data, 99.3 percent of the true genotypes are included in the 99.8 percent credible set, regardless of the number of donors that comprised the mixture. They also determined that the most probable genotype was the true genotype for 97 percent of the loci when the number of cells in a cluster was at least two. Since efficient investigative leads will be borne by posterior mass distributions that are narrow and concentrated at the true genotype, the authors report that, for this test set, 47,900 (86 percent) loci returned only one credible genotype and of these 47,551 (99 percent) were the true genotype. When determining the LR for true contributors, 91 percent of the clusters rendered LR>1018, showing the potential of single-cell data to positively affect investigative reporting. (Published Abstract Provided)